Related papers: CNN-Based Online Trigger for QGP Event Selection
The hot, dense and strongly interacting medium known as the Quark Gluon Plasma (QGP) is produced in relativistic heavy-ion collisions at the Large Hadron Collider (LHC). Early in the collisions, quarks and gluons from the incoming nuclei…
A sophisticated trigger system, capable of real-time track reconstruction, is used in the ATLAS experiment to select interesting events in the proton-proton collisions at the Large Hadron Collider at CERN. A set of $b$-jet triggers was…
The different modifications of quark- and gluon-initiated jets in the quark-gluon plasma (QGP) produced in heavy-ion collisions is a long-standing question that has not yet received a definitive answer from experiments. In particular, the…
The study of correlations between opposite-sign charge pairs and particle-ratio fluctuations can provide a powerful tool to probe the properties of the quark-gluon plasma (QGP). It has been suggested that the existence of a QCD phase…
In this study, Au+Au collisions with the impact parameter of $0 \leq b \leq 12.5$ fm at $\sqrt{s_{NN}} = 200$ GeV are simulated by the AMPT model to provide the preliminary final-state information. After transforming these information into…
In modern nuclear physics experiments, identifying events of interest is challenging for nuclear reaction studies with the active target Time Projection Chamber (TPC). In this work, machine learning techniques are employed to analyze the…
Phasor measurement units (PMUs) are being widely installed on power systems, providing a unique opportunity to enhance wide-area situational awareness. One essential application is the use of PMU data for real-time event identification.…
The implications of parton rearrangement processes on the dynamics of ultra-relativistic heavy-ion collisions have been investigated. A microscopic transport approach, namely the quark gluon string model (QGSM) which has been extended for a…
Graphs are a fundamental representation of complex, nonlinear structured data across various domains, including social networks and quantum systems. Quantum Graph Recurrent Neural Networks (QGRNNs) have been proposed to model quantum…
A new method of event characterization based on Deep Learning is presented. The PointNet models can be used for fast, online event-by-event impact parameter determination at the CBM experiment. For this study, UrQMD and the CBM detector…
Relativistic heavy ion collisions, which are performed at large experimental programs such as Relativistic Heavy Ion Collider's (RHIC) STAR experiment and the Large Hadron Collider's (LHC) experiments, can create an extremely hot and dense…
A web-based tool called ADFilter was developed to process collision events using autoencoders based on a deep unsupervised neural network. The autoencoders are trained on a small fraction of either collision data or Standard Model Monte…
Graph neural networks are increasingly adopted in trigger systems for collider experiments, where strict latency and throughput constraints render deployment on embedded platforms challenging. As detectors move towards higher granularity,…
I review recent developments in the phenomenological study of the quark-gluon plasma (QGP) transport properties based on a personal selection of results that were presented at Quark Matter 2019. The constraints on the temperature dependence…
We developed an efficient classifier that sorts alpha-decay events from various vertex-like objects in nuclear emulsion using a convolutional neural network (CNN). Alpha-decay events in the emulsion are standard calibration sources for the…
The modification of quark- and gluon-initiated jets in the quark-gluon plasma produced in heavy-ion collisions is a long-standing question that has not yet received a definitive answer from experiments. In particular, the size of the…
Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the…
This work presents a Bayesian inference study for relativistic heavy-ion collisions in the Beam Energy Scan program at the Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)D collision dynamics using…
We discuss the physics underlying event-by-event fluctuations in relativistic heavy ion collisions. We will emphasize how the fluctuations of particle ratios can be utilized to explore the properties of the matter created in these…
PEGASUS is a parton-level Monte-Carlo event generator designed to calculate cross sections for a wide range of hard QCD processes at high energy $pp$ and $p\bar p$ collisions, which incorporates the dynamics of transverse momentum dependent…